Quantifying the internationality and multidisciplinarity of authors and journals using ecological statistics
Quantifying the internationality and multidisciplinarity of authors and journals using ecological statistics
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DOI：
10.1007/s11192-018-2692-z
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发表时间：
2018-05-01
期刊：
影响因子：
3.9
通讯作者：
Wardell-Johnson, Grant
中科院分区：
文献类型：
--
作者：
Calver, Michael;Bryant, Kate;Wardell-Johnson, Grant
作者或期刊经常根据断言或定性证据声称国际化或多学科，而科学计量学研究则使用超出偶尔用户资源的复杂分析或软件来评估这些概念。本文展示了如何将用于描述生态群落的统计学应用于文献计量学数据，以量化个人和期刊的国际性或多学科性，从而能够使用图形用户界面免费软件进行统计意义的测试，即使是临时用户也可以访问。可以计算Margalef丰富度、多样性和均衡性或公平性，以表明论文或引文主要来自一小部分国家或学科，还是分布更广。对作者或期刊之间Margalef丰富度、多样性或均衡性的差异进行统计学意义的检验，可以检验不同的假设，例如：作者之间或期刊之间的国际性或多学科差异；或作者或期刊这些变量随时间的变化(可能是为了应对职业变化或编辑政策的变化)。以许多潜在用户可以接受的方式量化国际性和多学科，并有可能进行统计假设检验，一方面是对断言和定性描述的重大进步，另一方面是对概念和实践上的复杂分析的重大进步。
Authors or journals often claim internationality or multidisciplinarity based on assertion or qualitative evidence, while scientometric studies employ sophisticated analyses or software beyond the resources of occasional users to assess these concepts. This paper demonstrates how statistics used to describe ecological communities can be applied to bibliometric data to quantify internationality or multidisciplinarity for individuals and journals, enabling tests of statistical significance using graphical user interface freeware accessible to even occasional users. Margalef Richness, diversity and evenness or equitability can be calculated to indicate whether papers or citations come predominantly from a small group of countries or disciplines, or are more widely distributed. Tests of statistical significance for differences in Margalef richness, diversity or evenness between authors or journals enable testing of diverse hypotheses including, for example: differences in internationality or multidisciplinarity between authors or between journals; or changes over time in these variables for authors or journals (perhaps in response to career changes or changes in editorial policy). Quantifying internationality and multidisciplinarity in an accessible way for many potential users, with the possibility of statistical hypothesis testing, is a significant advance over assertion and qualitative description on the one hand or conceptually and practically complex analysis on the other.